Wearable device electrocardiogram

ABSTRACT

Provided are a method and systems for measuring an electrocardiogram (ECG) using a wearable device. An example system includes the wearable device in a shape of a band worn on a limb (e.g., a wrist) of a patient. The wearable device includes an electrical sensor. The wearable device is operable to record, via the at least one electrical sensor, an electrical signal from the limb of the patient. The wearable device is operable to split the electrical signal into segments based on a reference signal. The reference signal includes an indication of onset times of heart beats. The segments are averaged to derive average ECG data of low signal-to-noise ratio. The wearable device includes an optical sensor operable to measure skin color beneath a pulsating artery of the limb. The reference signal includes a photoplethysmogram (PPG) signal recorded via the optical sensor simultaneously with the electrical signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is related to U.S. patent application Ser. No.14/738,666 titled “Monitoring Health Status of People Suffering fromChronic Diseases” filed on Jun. 12, 2015 and U.S. patent applicationSer. No. 14/738,711 titled “Pulse Oximetry” filed on Jun. 12, 2015. Thesubject matter of the aforementioned applications is incorporated hereinby reference for all purposes.

FIELD

The present application relates to systems and methods for monitoringhealth status of people suffering from chronic diseases, and morespecifically to measuring an electrocardiogram (ECG) with a wearabledevice.

BACKGROUND

It should not be assumed that any of the approaches described in thissection qualify as prior art merely by virtue of their inclusion in thissection.

An ECG represents electrical activity of a heart. Traditionally, an ECGis recorded by placing surface electrodes at multiple locations of apatient's body (for example, 12 locations in a 12-lead system).

An ECG is used to measure the heart's electrical activity, generated bythe polarization and depolarization of cardiac tissue, and to translatesuch electrical activity into an electrical waveform. The ECG waveformcan provide information concerning the rate and regularity ofheartbeats; size and position of the chambers, and can indicate thepresence of damage to the heart muscle. The ECG waveform measurementscan be used to analyze the effects of drugs or devices, such as, forexample, the effect of a beta-blocker medication on cardiac arrhythmiapathologies, or the effect of a pacemaker, used to regulate the heart.

The ECG waveform can often detect heart disease, heart attack, anenlarged heart, or abnormal heart rhythms that may cause heart failure.Particularly, certain changes in the ECG waveform may be indicative oflife-threatening medical conditions, such as, for example, a myocardialinfarction, an acute coronary ischemia, a ventricular hypertrophy, apulmonary embolism, and so forth.

In clinical settings, multiple channels can be used to capture differentvectors of electrical activity of a beating heart. Monitoring patientsout of hospital using a one-lead electrocardiography has proved toprovide valuable health status information. Monitoring chronically illpatients outside a hospital environment is crucial for detecting earlyonset of symptoms and negative progression of chronic diseases.

Some existing wearable ECG systems include sensing capabilities embeddedin vests or shirts. Existing wearable devices wearable are generallydesigned for measuring heart rates during exercise and do not providesophisticated analysis of heart activity. Furthermore, while making ECGmeasurements from a wrist, ankle, or neck is possible, it generallyrequires closing an electric circuit around the heart using another bodypart. For example, a patient may be required to close the electriccircuit by touching a wrist worn device with the other hand. Therequirement of the patient's active participation in the measurementprocess can limit the practical usability of the wearable device.

Therefore, a need exists to receive ECG measurements using a wearabledevice without requiring the patient to take an active role in themeasurement process.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

According to one aspect of the present disclosure, a system formeasuring ECG data using a wearable device is provided. The wearabledevice can include at least one electrical sensor. The wearable devicecan be configured to record, via the at least one electrical sensor, anelectrical signal from a wrist of a patient. It should be noted,however, that the embodiments of the present disclosure are not limitedto the wrist and other parts of a human body such as ankles or neck canbe used. The electrical signal can include an ECG signal and a noise.The wearable device can be further operable to split the electricalsignal into segments based on a reference signal. The reference signalcan include an indication of onset times of heart beats, or otherfiducial timing information relating to heart beat. The wearable devicecan be further operable to average the segments to derive an average ECGdata.

The wearable device can further include an optical sensor. The opticalsensor can be operable to measure a color of skin beneath a pulsatingartery of the wrist. In certain embodiments, the reference signal is aphotoplethysmogram (PPG) signal recorded via the optical sensorsimultaneously with the electrical signal. In some embodiments, thereference signal is a first derivative of a PPG signal recorded via theoptical sensor simultaneously with the electrical signal.

In various embodiments, prior to the averaging, the segments aredistributed into groups. Each group can include segments correspondingto a certain heart rate. The averaging can include averaging segmentsbelonging to at least one of the groups.

In some embodiments, the electronic sensor includes a first input platedisposed at a proximity of an inner side of a wrist and a second inputplate disposed at a proximity of an outer side of the wrist. In certainembodiments, the electronic sensor includes two input plates located onopposite sides of the wrist.

The wearable device is most commonly embodied in the form of awristband, a watch, or a bracelet configured to be worn on the wrist.The device may be configured to be worn on any other suitable part ofthe body of the user.

The wearable device is configured to analyze average ECG data recordedover an extended period of time to determine trends in parameters of theaverage ECG data. The wearable device can be further operable todetermine, based at least on the trends, at least one possible symptomor a probable progression of at least one chronic heart disease. Thewearable device can be configured to provide reports and warningmessages regarding the at least one possible symptom and the probableprogression. In some embodiments, the segments are intervals between twosubsequent heart beats.

According to another aspect of the present disclosure, a method formeasuring an ECG using a wearable device is provided. The methodincludes recording, via at least one electrical sensor associated withthe wearable device, an electrical signal from a wrist of a patient. Theelectrical signal includes an ECG signal and a noise. The method allowssplitting the electrical signal into segments based on a referencesignal. The reference signal includes an indication of times at whichheart beats occur. The method can also include averaging the segments toderive average ECG data. In some embodiments, the method can furtheranalyze the average ECG data recorded over an extended period of time todetermine trends in parameters of the average ECG data. The method caninclude determining, based at least on the trends, at least one possiblesymptom or a probable progression of at least one chronic heart disease.The method can also include providing at least one of the following: areport and a warning message regarding the at least one possible symptomand the probable progression.

According to another example embodiment of the present disclosure, thesteps of the method for measuring ECG data using a wearable device arestored on a non-transitory machine-readable medium comprisinginstructions, which when implemented by one or more processors performthe recited steps.

Other example embodiments of the disclosure and aspects will becomeapparent from the following description taken in conjunction with thefollowing drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are illustrated by way of example and not limitation in thefigures of the accompanying drawings, in which like references indicatesimilar elements.

FIG. 1 is a block diagram showing an example system for measuring ECGdata using a wearable device.

FIG. 2 is a block diagram showing components of an example device formeasuring ECG data using the wearable device.

FIG. 3A is a schematic diagram illustrating an example device formeasuring ECG data using the wearable device.

FIG. 3B is a schematic diagram showing an example optical sensor.

FIG. 4 shows example plots of noisy ECG a data, a “clean” ECG waveform,and a PPG derivative.

FIG. 5 is a flow chart showing an example method for measuring ECG datausing the wearable device.

FIG. 6 shows example plots of a raw PPG signal, a filtered PPG signal,an electrical signal from the left wrist, average ECG fata from the leftwrist, and average differential ECG data.

DETAILED DESCRIPTION

The following detailed description includes references to theaccompanying drawings, which form a part of the detailed description.The drawings show illustrations in accordance with exemplaryembodiments. These exemplary embodiments, which are also referred toherein as “examples,” are described in enough detail to enable thoseskilled in the art to practice the present subject matter. Theembodiments can be combined, other embodiments can be utilized, orstructural, logical and electrical changes can be made without departingfrom the scope of what is claimed. The following detailed descriptionis, therefore, not to be taken in a limiting sense, and the scope isdefined by the appended claims and their equivalents.

The present disclosure provides systems and methods for measuring ECGdata using a wearable device. Embodiments of the present disclosure canallow measuring ECG data of a patient in a non-intrusive manner while,for example, the patient is at home, at work, outdoors, traveling, or islocated at some other stationary or mobile environment. Some embodimentsof the present disclosure include the wearable device that the patientwears around a wrist. The wearable device allows measuring ECG data froma wrist of the patient without requiring the patient to take an activerole in the process. The ECG data collected during an extended period oftime can be analyzed to detect and track trends and to make conclusionsconcerning symptoms and a progression of one or more chronic diseasesfrom which the patient might suffer.

According to some example embodiments, a method for measuring ECG datausing a wearable device includes recording an electrical signal from apatient's wrist. The electrical signal can be recorded via at least oneelectrical sensor associated with the wearable device. The electricalsignal can include an ECG signal and a noise. The method allowssplitting the electrical signal into segments. The splitting can bebased on a reference signal. The reference signal can include anindication of onset times of heart beats. The method can includeaveraging the segments to derive average ECG data.

Referring now to FIG. 1 , an example system 100 for measuring ECG datausing a wearable device is shown. The system 100 includes at least thewearable device 110. The wearable device can include sensors 120. Insome embodiments, the wearable device 110 is worn by a patient 130 (forexample, on a wrist) for an extended period of time. The wearable device110 can be carried out as a watch, a bracelet, a wristband, and thelike.

The wearable device 110 can be operable to constantly collect, viasensors 120, sensor data from a patient 130. Based on the sensor data,the wearable device 110 can be operable to obtain ECG data associatedwith the patient 130.

In some embodiments, the system 100 includes a mobile device 140. Themobile device 140 can be communicatively coupled to the wearable device110. In various embodiments, the mobile device 140 is operable tocommunicate with the wearable device 110 via a wireless connection viawireless technology. The mobile device 140 can include a mobile phone, asmart phone, a phablet, a tablet computer, a notebook, and so forth. Themobile device 140 can be operable to receive the sensors data andanalyze the sensor data to generate ECG data.

In further embodiments, the system 100 may include a cloud-basedcomputing resource 150 (also referred to as a computing cloud). In someembodiments, the cloud-based computing resource 150 includes one or moreserver farms/clusters comprising a collection of computer servers and isco-located with network switches and/or routers. In certain embodiments,the mobile device 140 is communicatively coupled to the computing cloud150. The mobile device 140 can be operable to send the sensor data tothe computing cloud 150 for further analysis (for example, forextracting ECG data from the sensor data and storing the results). Thecomputing cloud 150 can be operable to run one or more applications andto provide reports regarding health status of the patient, based ontrends in ECG data over time. A doctor 170 treating the patient 130 mayaccess the reports (for example, via computing device 160) using theInternet or a secure network. In some embodiments, the results of theanalysis of the medical parameters can be sent back to the mobile device140.

FIG. 2 is a block diagram illustrating components of wearable device110, according to an example embodiment. The example wearable device 110includes sensors 120, a transmitter 210, a processor 220, memory 230,and a battery 240. The wearable device 110 may comprise additional ordifferent components to provide a particular operation or functionality.Similarly, in other embodiments, the wearable device 110 includes fewercomponents that perform similar or equivalent functions to thosedepicted in FIG. 2 .

The transmitter 210 can be configured to communicate with a network suchas the Internet, a Wide Area Network (WAN), a Local Area Network (LAN),a cellular network, and so forth, to send data streams (for examplesensor data, ECG data, and messages).

The processor 220 can include hardware and/or software, which isoperable to execute computer programs stored in memory 230. Theprocessor 220 can use floating point operations, complex operations, andother operations, including processing and analyzing sensor data, toextract ECG data.

In some embodiments, the battery 240 is operable to provide electricalpower for operation of other components of the wearable device 110. Insome embodiments, the battery 240 is a rechargeable battery. In certainembodiments, the battery 240 is recharged using an inductive chargingtechnology.

In various embodiments, the sensors 120 include at least one electricalsensor 224 and at least one optical sensor 222. In certain embodiments,the sensor 120 can include position and motion sensors. The motionsensors can include an accelerometer, gyroscope, and InertialMeasurement Unit (IMU).

FIG. 3A is a schematic diagram illustrating an example wearable device110 placed around the left wrist 310 of a patient. In the example ofFIG. 3A, the wearable device 110 is carried in a shape of a watch, aring and/or a bracelet.

The electrical sensor 224 can include a differential amplifier operableto measure the electrical signal from the wrist 310. The electricalsensor 224 can include two active amplifier input plates embedded in thewearable device at opposite ends. In some embodiments, the first inputplate (not shown) can be placed above the outer side of the wrist, andthe second input plate 340 a can be placed beneath the inner side of thewrist 310. Alternatively or additionally, in other embodiments, theinput plates 350 a and 350 b can be placed in contact with,respectively, the left and right sides of the wrist 310.

In some embodiments, the optical sensor 222 can be placed beneath apulsating artery travelling along the arm and into the wrist 310. Insome embodiments, the radial artery 320 passing in the inner wrist isused for measurements by the optical sensor 222. In other embodiments,other arteries such as the ulnar artery may be used. An external lightsource generating constant lighting can be used to radiate the pulsatingartery. A beam reflected form the pulsating artery can be intercepted bythe optical sensor 222. In certain embodiments, red lighting is used toradiate the pulsating artery. Alternatively, in other embodiments, otherlighting, for example white lighting, can be used.

FIG. 3B is a schematic diagram showing an optical sensor 222, accordingto an example embodiment. The optical sensor 222 can include multiplelight sensors 360 (for example, photoelectric cells) to measure thereflected light. The pulsating artery can be irradiated by multiplelight transmitters 370 (for example, Light Emission Diodes (LEDs)). Thenumber and location of the light sensors and light transmitters can bechosen in a way that if, accidentally, the wearable device 110 slidesoff, at least one of the light sensors is still located sufficientlyclose to the pulsating artery. In some embodiments, when measuring thelight reflected from the pulsating artery, a signal from thosephotoelectric cells that provides the strongest output can be selectedfor further processing.

FIG. 4 shows plots of an example electrical signal 410 measured from onewrist (or some other limb), an example plot of “clean” ECG signal 420,and a plot of first derivative 430 of a PPG signal. The electricalsignal can be recorded with electrical sensor 224 using input platesplaced on the wearable device 110. Taking measurement from a single handor a single wrist can be challenging because the difference in voltagesbetween measured locations is miniscule. The electrical signal 410measured at the wrist can include an ECG signal and a noise. The noisecan be caused by muscle activity, patient movements, and so forth. Thenoise component can be larger than the ECG signal. In some embodiments,the signal-to-noise ratio (SNR) is in the range of −40 dB to −60 dB.

The “clean” ECG signal 420 is an imaginary ECG signal that can beobtained simultaneously with electrical signal 410 using a regular twoleads ECG recording, for example, when two input plates of a cardiographare placed at two different wrists of the patient. The “clean” ECGsignal 420 can include R peaks corresponding to heart beats. Using the“clean” ECG signal 420 as a reference, the electrical signal 410 can besplit in segments, with each of the segments T_(i) (i=1, 2, 3, . . . )corresponding to one RR interval (an interval between two successiveheart beats). Each segment T_(i) (i=1, 2, 3, . . . ) of an electricalsignal can contain an ECG signal s_(i)(t) and a noise componente_(i)(t). Assuming a stationary heartbeat waveform, if segments T_(i)(i=1, 2, 3, . . . ) are substantially of the same length, then ECGsignal s_(i)(t) is substantially of the same waveform when noisecomponents e_(i)(t) are not correlated to each other. The followingaveraging technique can be used to extract an ECG signal S(t) fromelectrical signal 410:S(t)=Σ_(i=1) ^(p)(s _(i)(t)+e _(i)(t)),wherein p is a number of segments T_(i) (i=1, 2, 3, . . . ) selected foraveraging. The segments T_(i) (i=1, 2, 3, . . . ) selected for averagingare measured for a pre-determined time period (for example, for a fewseconds or a few minutes). The segments selected for averaging aresubstantially of the same length.

The averaging increases the SNR in resulting average ECG signal S(t). Incertain embodiments, the SNR in resulted averaged ECG signal S(t) can befurther increased by weighted averaging, Wiener filtering, Adaptivefiltering, and with other techniques.

Since the “clean” ECG signal 420 is not available when the measurementsare carried out on a single wrist, a PPG signal can be used as areference signal to split the electrical signal 410 in segments. Invarious embodiments of the present disclosure, the PPG signal isrecorded using the optical sensor 222 simultaneously with the electricalsignal 410, which is recorded by the electrical sensor 224. The PPGsignal is obtained by sensing a change in the color of skin. The changeof the skin color is caused by a blood flow in the pulsating artery. Insome embodiments, the first derivative 430 of PPG signal can be used asa reference signal. The first derivative 430 of PPG signal can includesharp peaks R′ corresponding to the heart beats. Since it takes a timefor blood to flow from the heart to the wrists, the peaks R′ are shiftedby a time period A relative to the heart beats R in “clean” ECG signal420. Assuming that A is approximately the same for all heart beats, thepeaks R′ can be used to split the electrical signal 410 in segmentsT′_(i) (i=1, 2, 3, . . . ). In some embodiments, the averaging techniquecan be applied to segments T′_(i) (i=1, 2, 3, . . . ) of ECG data toincrease SNR. In other embodiments, the segments T′_(i) (i=1, 2, 3, . .. ) can be shifted by the time period A and the averaging can be appliedto the shifted segments.

In some embodiments, prior to the averaging, the segments of the ECGsignal can be split into groups. Each of these groups can includesegments of the ECG signal corresponding to a certain pulse rate atwhich the segments were measured. The pulse rate is provided based onmeasurements of the PPG signal. The averaging can be applied to eachgroup of segments independently.

In some embodiments, averaging can be performed on ECG data collectedwithin a pre-determined period of time (for example, during a day). Theaverage ECG data that is obtained by averaging segments collected duringa day can be further compiled and saved locally (in the memory ofwearable device 110 or mobile device 140) or remotely (in a memorystorage of computing cloud 150) for further analysis. The average datacan be analyzed to detect and track changes and trends in average ECGdata over an extended period of time. The extended period of time caninclude one or more weeks, one or more months, or even years.

In some embodiments, based at least on the trends, symptoms of one ormore chronic diseases are indicated due to their relationship withmeasured or derived parameters. In certain embodiments, reportsconcerning suspected progression of one or more chronic diseases can begenerated based on the trends. In some embodiments, based on thesymptoms, the patient can be advised to take palliative steps such astaking a medication and/or to contact a medical professional.

In various embodiments, processing electrical signal 410 and firstderivative 430 of PPG signal, analyzing average ECG data to detect andtrack trends, and generating reports on symptoms and progression ofchronic diseases can be performed locally on wearable device 110 and/ormobile device 140 and remotely in computing cloud 150.

It may be desirable to utilize the motion data obtained via the motionsensors to provide parameters of body movement and tremor. In certainembodiments the motion data can be used for performing a noise analysisto remove artifacts in ECG data.

In further embodiments, an accelerometer (a tri-axis accelerometer) canbe placed on skin near an artery of the patient and provide data onflexion of the artery due to blood flow. The data provided by theaccelerometer can be used to generate the ECG data.

The wearable device 110 can be configured to operate in at least twomodes. A first mode can include reading an ECG data from one wrist,synchronizing the ECG data with reference PPG data, segmenting andgrouping the ECG data to perform averaging ECG data to improve the SNR.

In a second mode, the wearable device can be configured to improve thePPG data based on ECG data as a reference signal. While operating thewearable device in the second mode, the patient can be asked to touchthe wearable device with other hand, in order to allow receiving a“two-handed” ECG data (good quality ECG data) which include much lessnoise than “a single wrist” ECG data. The wearable device can include anextra lead to receive input from other hand when touching. In the secondmode, poor PPG data can be segmented using the “two-handed” ECG data asa reference signal. The PPG segments can be dropped and averaged toreceive high quality PPG data. The high quality PPG data can be usedalong with good quality ECG data to estimate, for example, a pulsetravel time.

In some embodiments, the system 100 for measuring ECG data includes atleast one additional wearable device. The additional wearable device canbe identical to the wearable device 110. In some embodiments, patient130 may wear one of the devices throughout the day and another device atnighttime. In certain embodiments, the wearable device can be changedwhen the battery level drops below a certain level. The wearable devicethat is not in use at the moment can be recharged. In some furtherembodiments, the device can be recharged using induction chargingtechnology. In some embodiments, since both the devices are incommunication with mobile device 140, the replaced device can, at leastpartially, transmit recorded information (ECG data and PPG data) to thereplacing wearable device for synchronization. The information can bedownloaded to the mobile device 140 and the mobile device 140 can beoperable to send the information to the replacing device. Additionallyin other embodiments, the two wearable devices can be configured toexchange information (for example ECG data and PPG data) via thecomputing cloud 150.

FIG. 5 is a flow chart of a method 500 for measuring ECG data from usinga wearable device, according to an example embodiment. In block 510,method 500 includes recording an electrical signal from a wrist of apatient. The electrical signal can be recorded by at least oneelectrical sensor associated with the wearable device. The wearabledevice can be carried out in a shape of a watch, a bracelet, or awristband configured to be worn on the wrist of the patient. Theelectrical signal includes an ECG signal and a noise.

In block 520, the method 500 can include splitting the electrical signalinto segments based on a reference signal. The reference signal caninclude an indication of onset times of heart beats. In someembodiments, the reference signal includes a PPG signal recorded via anoptical sensor associated with the wearable device simultaneously withthe electrical signal. In certain embodiments, the reference signal isthe first derivative of a PPG signal recorded via the optical sensorsimultaneously with the electrical signal. The optical sensor can beconfigured to measure color of skin beneath a pulsating artery of thewrist.

In block 530, the method 500 proceeds to average the segments and toderive average ECG data. Averaging the segments improves the SNR in theelectrical signal.

Example

FIG. 6 illustrates plots of a raw PPG signal (optical signal) 610, afiltered PPG signal 620, an electrical signal 630, average ECG signals640 and 650, and an average differential ECG signal 660. Recordings ofthe electrical signal 630 and a raw PPG signal 610 can be simultaneouslymeasured at a wrist of a patient. The electrical signal 630 can bemeasured using a differential amplifier, and the optical signal 610 canbe measured with a photodiode detector placed beneath the radial artery.The raw PPG (optical) signal 610 can be processed to receive filteredPPG signal 620, yielding trigger points for the time-locked averaging ofthe ECG signal.

According to example measurements, an average 5 minute ECG signal and 15minute average ECG signal are shown to converge to a two-sided averageECG signal. The two-sided average ECG signal is measured from both sides(for example, from two different wrists of patient). The ECG complex isalready evident in a 5 minute average, yet a 15 minute recordingprovides a higher quality average waveform.

The present technology is described above with reference to exampleembodiments. Therefore, other variations upon the example embodimentsare intended to be covered by the present disclosure.

What is claimed is:
 1. A method for extracting an average ECG waveform,the method comprising: recording, via at least a first input plate and asecond input plate of at least one electrical sensor associated with awearable device, an electrical signal from a single wrist of a patient,the electrical signal including an ECG component and a noise component,wherein the first input plate and the second input plate are placed incontact with opposite sides of the single wrist of the patient;detecting a pulse of the patient and recording a photoplethysmogram(PPG) signal, via a PPG optical sensor associated with the wearabledevice, the electrical signal and the PPG signal being simultaneouslymeasured at the single wrist of the patient; generating, by a processorfrom the recorded electrical signal, electrical signal segments of therecorded electrical signal, the electrical signal segments beingtime-locked to the PPG signal by utilising the PPG signal as a referencesignal; and summing the electrical signal segments in a given timeperiod and dividing by a number of segments to produce an average ECGwaveform based on a subset of the electrical signal segments, resultingin a reduction of an uncorrelated noise component of the electricalsignal and an extraction of the average ECG waveform from the electricalsignal during the time period.
 2. The method of claim 1, wherein the PPGoptical sensor is further operable to measure a color of a skin above apulsating artery of the single wrist.
 3. The method of claim 2, whereinthe reference signal is recorded via the PPG optical sensorsimultaneously with the electrical signal.
 4. The method of claim 2,wherein the reference signal is a first derivative of the PPG signalrecorded via the PPG optical sensor simultaneously with the electricalsignal.
 5. The method of claim 1, wherein the processor is used todetect changes in the average ECG waveform over time.
 6. The method ofclaim 1, wherein the at least one electrical sensor includes a firstinput plate configured to be located on an inner side of the wrist and asecond input plate configured to be located on an outer side of thesingle wrist.
 7. The method of claim 1, wherein the processor is part ofthe wearable device.
 8. The method of claim 1, wherein the wearabledevice is carried out in a shape of one of the following: a wristband, awatch, and a bracelet configured to be worn on the wrist.
 9. The methodof claim 1, further comprising: analyzing, by the processor, the averageECG waveforms derived over a period of time to determine trends inparameters of the average ECG waveforms, wherein the period of timeincludes a pre-determined number of one or more of the following: weeks,months, and years; determining, by the processor and based at least onthe trends, at least one possible symptom or a probable progression ofat least one chronic heart disease; and providing at least one of areport and a warning message regarding the at least one possible symptomor the probable progression.
 10. A non-transitory computer-readablestorage medium having embodied thereon instructions, which when executedby a processor within a wearable device, perform steps of a method, themethod comprising: recording, via at least a first input plate of atleast one electrical sensor configured to be located at an inner side ofa wrist and a second input plate of at least one electrical sensorconfigured to be located at an outer side of the wrist, the first inputplate and the second input plate coupled with a wearable device, anelectrical signal from a single wrist of a patient, the electricalsignal including an electrocardiogram ECG component and a noisecomponent, wherein the first input plate and the second input plate areplaced in contact with opposite sides of the single wrist of thepatient; detecting a pulse of the patient and recording aphotoplethysmogram (PPG) signal, via a PPG optical sensor associatedwith the wearable device, the electrical signal and the PPG signal beingsimultaneously measured at the single wrist of the patient; generating,from the recorded electrical signal, electrical signal segments of theelectrical signal, the electrical signal segments being time-locked tothe PPG signal by utilising the PPG signal as a reference signal; andsumming the electrical signal segments in a given time period anddividing by a number of segments to produce an average ECG waveformbased on a subset of the electrical signal segments, resulting in areduction of an uncorrelated noise component of the electrical signaland an extraction of the average ECG waveform from the electrical signalduring the time period.
 11. The non-transitory computer-readable storagemedium of claim 10, wherein the PPG optical sensor is further operableto measure a color of a skin above a pulsating artery of the singlewrist.
 12. The non-transitory computer-readable storage medium of claim11, wherein the reference signal is recorded via the PPG optical sensorsimultaneously with the electrical signal.
 13. The non-transitorycomputer-readable storage medium of claim 11, wherein the referencesignal is a first derivative of the PPG signal recorded via the PPGoptical sensor simultaneously with the electrical signal.
 14. Thenon-transitory computer-readable storage medium of claim 10, wherein theprocessor is used to detect changes in the average ECG waveform overtime.
 15. The non-transitory computer-readable storage medium of claim10, wherein the wearable device is carried out in a shape of one of thefollowing: a wristband, a watch, and a bracelet configured to be worn onthe wrist.
 16. The non-transitory computer-readable storage medium ofclaim 10, the method further comprising: analyzing, by the processor,the average ECG waveforms derived over a period of time to determinetrends in parameters of the average ECG waveforms, wherein the period oftime includes a pre-determined number of one or more of the following:weeks, months, and years; determining, by the processor and based atleast on the trends, at least one possible symptom or a probableprogression of at least one chronic heart disease; and providing atleast one of a report and a warning message regarding the at least onepossible symptom or the probable progression.